Articles About Machine Learning

How to Kick Ass in Competitive Machine Learning

Last Updated on June 7, 2016 David Kofoed Wind posted an article to the Kaggle blog No Free Hunch titled “Learning from the best“. In the post, David summarized 6 key areas related to participating and doing well in competitive machine learning with quotes from top performing kagglers. In this post you will discover the key heuristics for doing well in competitive machine learning distilled from that post. Learning from the bestPhoto by Lida, some rights reserved Learning from Kaggle […]

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Going Beyond Predictions

Last Updated on June 7, 2016 The predictions you make with a predictive model do not matter, it is the use of those predictions that matters. Jeremy Howard was the President and Chief Scientist of Kaggle, the competitive machine learning platform. In 2012 he presented at the O’reilly Strata conference on what he called the Drivetrain Approach for building “data products” that go beyond just predictions. In this post you will discover Howard’s Drivetrain Approach and how you can use […]

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Master Kaggle By Competing Consistently

Last Updated on June 7, 2016 How do you get good at Kaggle competitions? It is a common question I get asked. The best advice for getting started and getting good is to consistently participate in competitions. You cannot help but get better at machine learning. A recent post by Triskelion titled “Reflecting back on one year of Kaggle contests” bares this out. He started out as a machine learning beginner and finished up as a “master” level Kaggle competitor […]

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5 Benefits of Competitive Machine Learning

Last Updated on June 7, 2016 Jeremy Howard, formally of Kaggle gave a presentation at the University of San Francisco in mid 2013. In that presentation he touched on some of the broader benefits of machine learning competitions like those held on Kaggle. In this post you will discover 5 points I extracted from this talk that will motivate you to want to start participating in machine learning competitions Competitive Machine Learning is a MeritocracyPhoto by PaulBarber, some rights reserved […]

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What is R

Last Updated on August 22, 2019 R is perhaps one of the most powerful and most popular platforms for statistical programming and applied machine learning. When you get serious about machine learning, you will find your way into R. In this post, you will discover what R is, where it came from and some of its most important features. Kick-start your project with my new book Machine Learning Mastery With R, including step-by-step tutorials and the R source code files […]

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Non-Linear Classification in R with Decision Trees

Last Updated on August 22, 2019 In this post you will discover 7 recipes for non-linear classification with decision trees in R. All recipes in this post use the iris flowers dataset provided with R in the datasets package. The dataset describes the measurements if iris flowers and requires classification of each observation to one of three flower species. Kick-start your project with my new book Machine Learning Mastery With R, including step-by-step tutorials and the R source code files […]

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Convex Optimization in R

Last Updated on August 22, 2019 Optimization is a big part of machine learning. It is the core of most popular methods, from least squares regression to artificial neural networks. In this post you will discover recipes for 5 optimization algorithms in R. These methods might be useful in the core of your own implementation of a machine learning algorithm. You may want to implement your own algorithm tuning scheme to optimize the parameters of a model for some cost […]

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Machine Learning Newsletters

Last Updated on June 7, 2016 There are a lot of blogs and videos on machine learning and more being created every day, week and month. If you are working or at school, it can feel overwhelming to keep up with some much material. Worse, you feel like you will be at some great disadvantage if you do miss something. In this post you will learn how subscribing to machine learning and data science newsletters can save you time and […]

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How To Estimate Model Accuracy in R Using The Caret Package

Last Updated on August 15, 2020 When you are building a predictive model, you need a way to evaluate the capability of the model on unseen data. This is typically done by estimating accuracy using data that was not used to train the model such as a test set, or using cross validation. The caret package in R provides a number of methods to estimate the accuracy of a machines learning algorithm. In this post you discover 5 approaches for […]

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How To Get Started With Machine Learning Algorithms in R

Last Updated on August 22, 2019 R is the most popular platform for applied machine learning. When you want to get serious with applied machine learning you will find your way into R. It is very powerful because so many machine learning algorithms are provided. A problem is that the algorithms are all provided by third parties, which makes their usage very inconsistent. This slows you down, a lot, because you have to learn how to model data and how […]

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